Oct data processing method, storage medium storing program for executing the oct data processing method, and processing device

ABSTRACT

To acquire information relating to a vessel wall thickness by: acquiring interference signal sets of a plurality of frames including interference signal sets corresponding to a plurality of frames forming an image of the same cross section of an fundus; generating 3-D tomographic image data on the fundus from the interference signal sets of the plurality of frames; generating 3-D motion contrast data in the fundus from the interference signal sets corresponding to the plurality of frames that form the same cross section; extracting a vessel from the fundus based on the 3-D tomographic image data or the 3-D motion contrast data; detecting a coordinate of an outer surface of a vessel wall of the vessel based on the 3-D tomographic image data; and detecting a coordinate of an inner surface of the vessel wall of the vessel based on the 3-D motion contrast data.

BACKGROUND

Field

The present disclosure relates to an OCT data processing method for OCTdata acquired by optical coherence tomography, a storage medium storinga program for executing the OCT data processing method, and a processingdevice.

Description of the Related Art

As a method of acquiring a tomographic image of an object to beinspected, for example, a living body, in a non-destructive andnon-invasive manner, optical coherence tomography has been put intopractical use. An OCT apparatus for executing the above-mentionedmethod, which is capable of acquiring a tomographic image of an objectto be inspected, for example, a retina in a fundus of an eye, is widelyused for ophthalmologic diagnosis of the retina or the like.

The OCT apparatus is configured to cause light reflected from the objectto be inspected and reference light to interfere with each other, andanalyze time dependence or wavenumber dependence of an intensity of theinterference light, to thereby acquire a tomographic image. As such OCTapparatus, there are known a time domain optical coherence tomography(TD-OCT) apparatus, a spectral domain optical coherence tomography(SD-OCT) apparatus, and a swept-source optical coherence tomography(SS-OCT) apparatus. The TD-OCT apparatus is configured to acquire depthinformation on the object to be inspected by changing an optical pathlength of the reference light by moving a reference mirror. The SD-OCTapparatus is configured to acquire the depth information by using lightemitted from a broadband light source. The SS-OCT apparatus isconfigured to acquire the depth information by using light emitted froma wavelength-tunable light source capable of changing an oscillationwavelength. The SD-OCT apparatus and the SS-OCT apparatus arecollectively referred to as “Fourier domain optical coherence tomography(FD-OCT) apparatus”.

In recent years, there has been proposed simulated angiography using theFD-OCT apparatus, which is referred to as “OCT angiography (OCTA)”. Influorescence angiography, which is general angiography in contemporaryclinical medicine, injection of a fluorescent dye (for example,fluorescein or indocyanine green) into a body is required. A brightregion through which the fluorescent dye passes is imaged, to therebydisplay a vessel two-dimensionally. However, a contrast medium mayproduce side effects including nausea, eruption, and coughing, and maycause shock symptoms on rare occasions. Hence, angiography involves somerisks. Meanwhile, OCTA enables non-invasive simulated angiographywithout a risk of injecting a foreign matter into the body, and enablesthree-dimensional display of a network of vessels. In addition, OCTA isattracting attention because OCTA is higher in resolution thanfluorescence angiography and can visualize minute vessels or blood flowof the fundus.

As OCTA, there are proposed a plurality of methods depending on adifference in manner of detecting a vessel region. For example, inFingler et al. “Mobility and transverse flow visualization using phasevariance contrast with spectral domain optical coherence tomography”Optics Express. Vol. 15, No. 20. pp. 12636-12653 (2007), there isproposed a method of extracting only signals with time modulation frominterference signals acquired by the OCT apparatus, to thereby separatethe interference signals caused by the blood flow. There are alsoproposed a method utilizing phase fluctuations due to the blood flow(“Speckle variance detection of microvasculature using swept-sourceoptical coherence tomography” Optics Letters Vol. 33, No. 13, pp.1530-1532 (2008)), a method utilizing intensity fluctuations due to theblood flow (Mariampillai et al., “Optimized speckle variance OCT imagingof microvasculature,” Optics Letters Vol. 35, No. 8, pp. 1257-1259(2010) or U.S. patent Application Publication No. 2014/221827), and thelike.

Currently, in medical sites, an examination of hypertension or the likeplaces an importance on observation of a change in hypertrophy of thevessel, which leads to arteriosclerosis, and there is a demand toacquire information relating to the hypertrophy of the vessel, that is,information on a vessel wall by a simple method.

SUMMARY

The present disclosure has been made in order to meet theabove-mentioned demand, and has an object to provide an OCT dataprocessing method capable of acquiring information relating to a vesselwall by using OCTA in a simplified manner, a storage medium storing aprogram for executing the OCT data processing method, and a processingdevice.

In order to solve the above-mentioned problem, according to oneembodiment of the present disclosure, there is provided an OCT dataprocessing method, including:

a signal acquiring step of acquiring interference signal sets of aplurality of frames including interference signal sets corresponding toa plurality of frames that form an image of the same cross section of anobject to be inspected;

generating 3-D tomographic image data on the object to be inspected fromthe interference signal sets of the plurality of frames;

generating 3-D motion contrast data based on a pixel with timemodulation in the object to be inspected from the interference signalsets corresponding to the plurality of frames that form the same crosssection;

extracting a vessel from the object to be inspected based on one of the3-D tomographic image data and the 3-D motion contrast data;

detecting a coordinate of an outer surface of a vessel wall of theextracted vessel based on the generated 3-D tomographic image data; and

detecting a coordinate of an inner surface of the vessel wall of theextracted vessel based on the generated 3-D motion contrast data.

Further features of the present disclosure will become apparent from thefollowing description of exemplary embodiments with reference to theattached drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic diagram for illustrating an example of an entireconfiguration of an OCT apparatus used in one embodiment of the presentdisclosure.

FIG. 2 is a diagram for illustrating a mode of scanning measuring lightaccording to this embodiment.

FIG. 3 is a flow chart for illustrating an example of an overallprocessing procedure according to this embodiment.

FIG. 4 is a flow chart for illustrating an example of a procedure foracquiring an interference signal according to this embodiment.

FIG. 5 is a flow chart for illustrating an example of a signalprocessing procedure for acquiring vessel information according to thisembodiment.

FIG. 6 is a flow chart for illustrating an example of a procedure foracquiring a vessel wall thickness according to this embodiment.

FIG. 7 is an explanatory diagram for illustrating an example of a methodof calculating the vessel wall thickness according to this embodiment.

FIG. 8 is a diagram for illustrating an example of a motion contrastimage according to this embodiment.

FIG. 9 is a diagram for illustrating an example of a display mode of avessel candidate on a GUI according to this embodiment.

FIG. 10 is a diagram for illustrating a method of acquiring informationon a vessel travel direction according to this embodiment.

FIG. 11 is a diagram for illustrating a method of detecting anabnormality in a vessel according to this embodiment.

DESCRIPTION OF THE EMBODIMENTS

Now, with reference to the accompanying drawings, an embodiment of thepresent disclosure is described in detail. In this embodiment, an SS-OCTapparatus is used to generate a tomographic image and a motion contrastimage described later from a 3-D optical coherence tomographic signalobtained from a fundus. Then, an inner surface and an outer surface of awall of a vessel (hereinafter referred to as “vessel wall”) in a retinaare detected from the tomographic image and the motion contrast imagethat have been obtained, and a vessel wall thickness is furthercalculated.

Configurations described in the following embodiment are merely anexample, and the present disclosure is not limited to the followingembodiment. Not all combinations of features described in the followingembodiment are necessarily essential to solutions of the presentdisclosure. In the embodiment, an object to be inspected is a human eye(fundus), but an object to which the present disclosure is applied isnot limited thereto. For example, the OCT apparatus may be used fordetecting a vessel in skin, an organ, or the like. Further, in theembodiment, an object to be imaged is the fundus of an eye, but anotherregion, for example, an anterior segment of the eye may be the object tobe imaged.

[Entire Configuration of Image Formation and Processing Device]

FIG. 1 is a diagram for illustrating a configuration example of an imageformation and processing device according to one embodiment of thepresent disclosure, which includes an OCT apparatus configured toacquire a 3-D optical coherence tomographic signal and a control unitconfigured to control the OCT apparatus and to process an opticalcoherence tomographic signal. Specifically, in FIG. 1, an opticalcoherence tomographic signal acquiring unit 100 and a control unit 143are illustrated.

<Configuration of Control Unit>

The control unit 143 includes a signal processing portion 144, a signalacquisition control portion 145, a display portion 146, and a displaycontrol portion 149. The signal processing portion 144 includes an imagegenerating portion 147 and a map generating portion 148. In this case,the control unit 143 is, for example, a computer, and a CPU included inthe computer is configured to execute a program stored in a storagedevice (not shown). This causes the computer to function as the signalprocessing portion 144, the signal acquisition control portion 145, theimage generating portion 147, the map generating portion 148, and thedisplay control portion 149.

The image generating portion 147 has a function of generating aluminance image and a motion contrast image from an electrical signal(interference signal) sent from a detector 141 of the optical coherencetomographic signal acquiring unit 100 described later. The mapgenerating portion 148 has a function of generating layer information(segmentation of a retina) from the luminance image. The signalacquisition control portion 145 is configured to control the respectiveportions described above. The signal processing portion 144 isconfigured to perform various kinds of processing on the interferencesignal, to perform various kinds of processing on the generated image,to analyze the images, and to generate visible information on analysisresults based on the interference signal output from the detector 141.

The images and the analysis results generated by the signal processingportion 144 are sent to the display control portion 149. The displaycontrol portion 149 is configured to display the images and the analysisresults on a display screen of the display portion 146. In this case, adisplay formed of, for example, a liquid crystal display is used as thedisplay portion 146. Image data generated by the signal processingportion 144 may be transmitted to the display portion 146 in a wired orwireless manner after being sent to the display control portion 149.Further, although the display portion 146 and other portions areincluded in the control unit 143 in this embodiment, the presentdisclosure is not limited thereto. The display portion 146 and otherportions may be provided separately from the control unit 143, and maybe, for example, a tablet computer, which is an example of a device thatcan be carried around by a user. In this case, it is preferred that thedisplay portion 146 be provided with a touch panel function, and beconfigured to enable operations to be performed on the touch panel formovement of a display position of the image, magnification or reductionof the image, change of the image to be displayed, and the like.

Any numbers of CPUs and storage devices may be included in the controlunit 143 as long as the numbers are at least one. That is, at least oneprocessing device (CPU) and at least one storage device (at least one ofa RAM and a ROM) are connected to the control unit 143. As a result,when at least one processing device executes the program stored in atleast one storage device, the control unit 143 functions as therespective portions described above. The processing device is notlimited to the CPU, and may be, for example, an FPGA.

<Configuration of Optical Coherence Tomographic Signal Acquiring Unit>

Next, description is given of a configuration of the optical coherencetomographic signal acquiring unit 100. FIG. 1 is a diagram forillustrating a configuration example of an OCT apparatus used as theoptical coherence tomographic signal acquiring unit in this embodiment.As the OCT apparatus, for example, an SD-OCT apparatus or an SS-OCTapparatus can be used. In this embodiment, the description is given ofthe configuration using the SS-OCT apparatus.

In the OCT apparatus, a swept-source (SS) light source is used as alight source 101. The light source 101 is configured to emit light whilesweeping a wavelength of the light with a sweeping central wavelength of1,050 nm and a sweeping width of 100 nm, for example. The values of thewavelength and the sweeping width are merely examples, and the presentdisclosure is not limited to those values. The same applies to thedescription of the following embodiment, that is, the describednumerical values are merely examples, and the present disclosure is notlimited to those numerical values.

The light emitted from the light source 101 is guided to a beam splitter110 via an optical fiber 102 to be split into measuring light andreference light. The split ratio of the beam splitter 110 is 90(reference light):10 (measuring light). The measuring light obtainedthrough splitting is output to a measuring optical path via an opticalfiber 111, and is converted into collimated light by a collimator 112.The measuring light converted into the collimated light enters an eye118 to be inspected via a scan system 114, a scan lens 115, and a focuslens 116. A shutter 85 is arranged behind the collimator 112, and isinserted into the measuring optical path at a time of acquiringbackground data described later. The scan system 114 is configured toscan the measuring light onto a fundus Er of the eye 118. In this case,the scan system 114 is illustrated as a single mirror, but actuallyincludes an X-axis scanner (not shown) and a Y-axis scanner (not shown)formed of galvano scanners so as to raster-scan the fundus Er of the eye118 with the measuring light. As those scanners, not only the galvanoscanners but also different kinds of known scanners, for example, aresonant scanner can be used.

The focus lens 116 is fixed on a stage 117, and is configured to move inan optical axis direction to adjust the focus of the measuring light.The scan system 114 and the stage 117 are controlled by the signalacquisition control portion 145 so that the measuring light can bescanned in a desired range of the fundus Er of the eye 118 (acquiringrange of a tomographic image).

It is desired that the OCT apparatus be provided with a trackingfunction of detecting movement of the fundus Er to cause the mirrors ofthe scan system 114 to scan the light while following the movement ofthe fundus Er. A general technology can be used to perform a method fortracking, and the method for tracking may be performed in real time, ormay be performed in post processing. As a method for tracking, there isgiven, for example, a method using a scanning laser ophthalmoscope(hereinafter referred to as “SLO”). In this method, a 2-D image of thefundus Er (fundus surface image) within a plane perpendicular to anoptical axis is acquired over time through use of SLO to extract acharacteristic portion within the image, for example, a portion in whicha vessel branches. How the characteristic portion within the acquired2-D image has moved is then calculated as a moving amount of the fundusEr, and the calculated moving amount is fed back to the scan system 114.By the above-mentioned steps, real-time tracking can be performed forthe movement of the fundus Er.

The measuring light is caused to enter the eye 118 by the focus lens 116fixed on the stage 117 to be focused on the fundus Er. The measuringlight irradiating the fundus Er is reflected or scattered at each layerof the retina, and travels on the above-mentioned measuring optical pathbackward as return light to return to the beam splitter 110. The returnlight entering the beam splitter 110 passes through an optical fiber 126to enter a beam splitter 128. The beam splitter 128 and the beamsplitter 110 described above may be a beam coupler.

The reference light obtained through splitting by the beam splitter 110is output to the reference optical path via an optical fiber 119 a, apolarization controller 150, and an optical fiber 119 b, and isconverted into collimated light by a collimator 120. The polarizationcontroller 150 can change the polarization of the reference light into adesired polarization state. The reference light further passes through adispersion compensation glass 122, an ND filter 123, and a collimator124 to enter an optical fiber 127. The collimator 124 and one end of theoptical fiber 127 are fixed on a coherence gate stage 125.

The coherence gate stage 125 is controlled by the signal acquisitioncontrol portion 145 so as to be driven in an optical axis directiondepending on the difference in ocular axis length among subjects to beexamined. Therefore, an optical path length of the reference light ischanged as the coherence gate stage 125 is driven. Interference lightdescribed later is obtained under a condition that the optical pathlength of the reference light and an optical path length of themeasuring light match each other. The optical path length of thereference light is changed in this embodiment, but the configuration forchanging the optical path length is not limited thereto as long as anoptical path length difference between the optical path of the measuringlight and the optical path of the reference light can be changed.

The reference light passing through the optical fiber 127 enters thebeam splitter 128. In the beam splitter 128, the return light of themeasuring light and the reference light are combined to obtaininterference light, and the interference light is further split into twobeams. The split interference light beams are interference light beamshaving phases inverted to each other (hereinafter expressed as apositive component and a negative component). The positive component ofthe split interference light passes through an optical fiber 129 toenter one input port of the detector 141. Meanwhile, the negativecomponent of the interference light passes through an optical fiber 130to enter another port of the detector 141. The detector 141 is adifferential detector in which, when two interference light beams havingphases inverted to each other by 180° are input, a DC component isremoved, and the interference signal having only an interferencecomponent is output. The differential detector is used as a detector inthis embodiment, but the mode of the detector is not limited thereto,and different kinds of known detectors can be used.

The interference light detected by the detector 141 is output as anelectrical signal (interference signal) corresponding to the intensityof the light. The output interference signal is input to the signalprocessing portion 144, which is an example of a tomographic imagegenerating portion.

[Scan Pattern]

In the OCT apparatus, measuring light scanning of radiating themeasuring light to one point on the fundus of the eye 118 to acquireinformation relating to a cross section of the fundus at the one pointin its depth direction is referred to as an A-scan. Further, measuringlight scanning for acquiring information relating to a cross section ofthe eye 118 along a scanning plane in one direction, which is adirection orthogonal to the A-scan, that is, a 2-D image regarding aplane formed of the one direction and a depth direction is referred toas a B-scan. In addition, measuring light scanning in a directionorthogonal to both scanning directions for the A-scan and the B-scan(orthogonal to the plane of the 2-D image) is referred to as a C-scan.

In the OCT apparatus, when the measuring light is two-dimensionallyraster-scanned on the fundus in order to acquire a three-dimensionaltomographic image of the fundus, high-speed scanning is performed in theB-scan direction. Further, low-speed scanning is performed in the C-scandirection in order to scan the measuring light such that the scanninglines of the B-scan are aligned in a direction orthogonal to the B-scandirection. A two-dimensional tomographic image in the depth directioncan be obtained by performing the A-scan and the B-scan, and athree-dimensional tomographic image can be obtained by performing theA-scan, the B-scan, and the C-scan. The measuring light is scanned inthe B-scan and the C-scan by the above-mentioned scan system 114.

The X-axis scanner (not shown) and the Y-axis scanner (not shown) areformed of deflecting mirrors arranged so as to have their respectiverotary axes orthogonal to each other. The X-axis scanner is configuredto perform scanning in the X-axis direction through use of the measuringlight, and the Y-axis scanner is configured to perform scanning in theY-axis direction through use of the measuring light. The respectivedirections of the X-axis direction and the Y-axis direction aredirections orthogonal to the direction of an ocular axis of an eyeballand orthogonal to each other. Such directions of line scanning as theB-scan direction and the C-scan direction may not necessarily match theX-axis direction and the Y-axis direction. Therefore, the directions forthe line scanning of the B-scan and the C-scan can be determinedappropriately depending on a 2-D tomographic image or a 3-D tomographicimage to be acquired.

Next, an example of a scan pattern of the measuring light of thisembodiment is described with reference to FIG. 2.

In OCTA, in order to measure the change with time of the OCTinterference signal due to the blood flow, measurement is required to beperformed a plurality of times at the same position (or substantiallythe same position). In this embodiment, the OCT apparatus performsscanning of repeating the B-scan at the same position m times, and thenmoving the scanning position of the measuring light to n y-positions. Aspecific scan pattern is illustrated in FIG. 2. At each of the ny-positions of y1 to yn on the fundus plane, the B-scan is repeated mtimes.

In order to correctly measure the change with time of the interferencesignal, those m times of B-scan are required to be performed at the sameposition on the fundus. However, the eye to be inspected always performsinvoluntary eye movement during fixation, and hence the measuring lightscanning at the same position is actually not easy even when scanning isintended on the same scanning line. The measuring light scanning that isperformed with the intention to B-scan the measuring light on thesame-position scanning line is herein referred to as scanning themeasuring light on the same scanning line, or acquiring the interferencesignal of the same cross section. Further, it is conceivable to executethe B-scan a plurality of times while slightly shifting the scanningline intentionally, and perform averaging or other processing on theobtained interference signals regarding pixels corresponding thereto, tothereby reduce noise. In this case, those substantially equal scanninglines of the measuring light are expressed as the same scanning line,and further, the tomographic image obtained through the averaging orother processing is also expressed as the tomographic image obtainedfrom the same scanning line.

In this case, as the value of m, which is the number of repetitiontimes, becomes larger, the number of measurement times at the sameposition also increases, and hence an accuracy of detecting the bloodflow increases. Meanwhile, the scan time increases, and hence therearise fears that a motion artifact occurs in an image due to movement ofan eye (involuntary eye movement during fixation) during a scan and thatburden on the subject to be examined increases. In this embodiment, thenumber of repetition times m is determined as 4 in consideration of thebalance between the detection accuracy and the measurement time. Thecontrol unit 143 may change m depending on an A-scan speed of the OCTapparatus, results of motion analysis of a fundus surface image of theeye 118, or the like.

In FIG. 2, p represents the number of samples of the A-scan in oneB-scan. In other words, the size of the plane image is determined basedon p×n. As p×n increases, a wider range can be scanned as long as ameasurement pitch is the same. However, the scan time increases, andhence the above-mentioned motion artifact and increase in the burden onthe subject to be examined are required to be taken into consideration.In this embodiment, n=p=300 is set in consideration of a balance betweenthe scan range and the scan time. The above-mentioned n and p can befreely changed as appropriate.

Further, Δx of FIG. 2 is an interval (x-pitch) between x-positions thatare adjacent A-scan positions, and Δy of FIG. 2 is an interval (y-pitch)between y-positions that are adjacent B-scan positions. In thisembodiment, the x-pitch and the y-pitch are determined as ½ of a beamspot diameter of the irradiation light on the fundus, and is set to 10μm. The image to be generated can be formed with high definition bysetting the x-pitch and the y-pitch to ½ of the beam spot diameter onthe fundus. Even when the x-pitch and the y-pitch are set smaller than ½of the beam spot diameter on the fundus, an effect of increasing thedefinition of the image to be generated to a level higher than that issmall.

When the x-pitch and the y-pitch are set larger than ½ of the beam spotdiameter on the fundus, the definition deteriorates, but a wide-rangeimage can be acquired with a small data volume. Therefore, the x-pitchand the y-pitch may be changed freely depending on clinical demands. Inthis embodiment, the scan range is set to p×Δx=3 mm in an x directionand n×Δy=3 mm in a y direction in consideration of the above.

Next, with reference to a flow chart of FIG. 3, description is given ofa procedure of specific processing executed by the processing deviceaccording to this embodiment. In Step S101, the signal acquisitioncontrol portion 145 controls the optical coherence tomographic signalacquiring unit 100 to acquire an optical coherence tomographic signal.Details of the processing are described later. Next, in Step S102, thecontrol unit 143 generates 3-D vessel information. Details of theprocessing are described later. In the processing device according tothis embodiment, the above-mentioned steps are carried out to acquire ordisplay information relating to a wall thickness of a designated vesselon the fundus, and then processing of generating the 3-D vesselinformation is completed. The description of this embodiment is directedto a case where the interference signal obtained from the eye 118 isprocessed in real time to obtain information on the vessel wall.However, data relating to the eye 118, which is acquired and stored in amemory or the like in advance, may be read to perform theabove-mentioned processing.

[Procedure for Acquiring Optical Coherence Tomographic Signal]

Next, with reference to a flow chart of FIG. 4, description is given ofa procedure of specific processing involving the acquisition of theoptical coherence tomographic signal performed in Step S101 according tothis embodiment. In this processing, first in Step S109, the signalacquisition control portion 145 sets an index i of a position yiillustrated in FIG. 2 to 1. In Step S110, the optical coherencetomographic signal acquiring unit 100 moves the radiating position ofthe measuring light based on an instruction from the signal acquisitioncontrol portion 145 so that the position for executing the B-scanbecomes yi. In Step S119, the signal acquisition control portion 145sets an index j of the repeated B-scans to 1. In Step S120, OCT startsthe repeated B-scans at the position yi.

In Step S130, the detector 141 detects the interference signal in eachA-scan, and the interference signal is stored in the signal processingportion 144 via an A/D converter (not shown). The signal processingportion 144 acquires p samples of interference signals obtained in theA-scans, to thereby set the p samples of interference signals as aninterference signal corresponding to one B-scan. When the first B-scanis completed at the position yi, in Step S139, the signal acquisitioncontrol portion 145 increments the index j of the repeated B-scans.

In Step S140, the signal acquisition control portion 145 determineswhether or not j is larger than a predetermined number of times (m).That is, the signal acquisition control portion 145 determines whetheror not the B-scan at the position yi has been repeated m times. When itis determined that the B-scan has not been repeated m times, the flowreturns to Step S120 to repeat the B-scan on the scanning line at thesame position, and the operation from Step S120 to Step S139 isrepeated. When it is determined that the B-scan has been repeated mtimes being the predetermined number of times, the flow proceeds to StepS149.

In Step S149, the signal acquisition control portion 145 increments theindex i of the position yi. In Step S150, the signal acquisition controlportion 145 determines whether or not i is larger than a predeterminednumber of times n, that is, whether or not the B-scan has been carriedout at all of the n y-positions. When it is determined that thepredetermined number of times of measurement has not been reached, theflow returns to Step S110 to carry out a B-scan at the next y-position,and the subsequent steps from Step S119 to Step S149 are repeated. Whenthe predetermined number of times of measurement at the y-position arecompleted (when yes), the flow proceeds to the next Step S160.

In Step S160, the optical coherence tomographic signal acquiring unit100 acquires, for the interference signals obtained individually,background data corresponding to noise ascribable to an apparatus or thelike. Specifically, the optical coherence tomographic signal acquiringunit 100 acquires data based on 100 A-scans without obtaining the returnlight under a state in which the shutter 85 is inserted into themeasuring optical path. The signal acquisition control portion 145averages the data obtained in the 100 A-scans, and stores the data. Thenumber of times of measuring a background is not limited to 100. Afterthe acquisition of the background data, a procedure for acquiring theoptical coherence tomographic signal is completed. In the same manner asthe data relating to the eye 118, which is stored as described above,data stored in a memory or the like in advance may be read to be used asthe optical coherence tomographic signal including the background data.

An interference signal set corresponding to one frame of the tomographicimage is obtained from the one B-scan described above. The interferencesignal sets corresponding to a plurality of frames that form the samecross section are obtained from m times of B-scan described above. Whenm times of B-scan are to be performed to acquire motion contrast datadescribed later in OCTA, the measurement requires a longer time asdescribed above. In addition, the repetition is not performed in normalOCT, and hence it is possible to acquire the data in a larger range inthe same amount of time as in OCTA. Therefore, compared with a regionfor performing OCTA, a region for acquiring 3-D tomographic image databy the OCT apparatus is often set to a larger region including theregion for OCTA. In this case, it is possible to reduce the measurementtime by including the above-mentioned interference signal sets for OCTAcorresponding to the plurality of frames in the interference signal setsof a plurality of frames for generating the 3-D tomographic image datato simultaneously acquire the interference signal sets. Theabove-mentioned acquisition of the interference signal sets is executedby the configuration functioning as a signal acquiring unit includingthe detector 141 and the signal acquisition control portion 145.

[Procedure for Processing of Generating 3-D Vessel Information]

Next, with reference to the flow chart of FIG. 5, description is givenof a procedure of specific processing involving the generation of the3-D vessel information performed in Step S102 described above. In thisembodiment, a motion contrast for OCTA needs to be calculated in orderto generate the 3-D vessel information from OCTA information describedlater.

In this case, the motion contrast is defined as a contrast between atissue involving flowing (for example, blood) and a tissue involving noflowing among tissues of the subject to be examined. Specifically, animage indicating a character amount, for example, a degree of dispersionof pixels of a portion with time modulation among a plurality oftomographic images of the same cross section, is referred to as a motioncontrast image. Further, a pixel value for the motion contrast image isdefined as a motion contrast. The motion contrast, a method of acquiringthe motion contrast, and the like, which are referred to in thisembodiment, are described later.

In this processing, first in Step S210, the signal processing portion144 sets the index i of the position yi to 1. In Step S220, the signalprocessing portion 144 extracts the interference signals correspondingto m times (B-scan data), which have been obtained by the repeatedB-scans at the position yi, from the data stored in a storage portion,for example, a memory (not shown). In Step S230, the signal processingportion 144 sets the index j of the repeated B-scans to 1. In Step S240,the signal processing portion 144 extracts the j-th B-scan data.

In Step S250, the signal processing portion 144 performs generalreconstruction processing on the B-scan data extracted in Step S240, tothereby generate a luminance image of the tomographic image. In thegeneration of the luminance image, the image generating portion 147first removes fixed pattern noise formed of the background data from theinterference signal. The fixed pattern noise is removed by averaging theA-scan signals of a plurality of pieces of detected background data toextract the fixed pattern noise and subtracting the fixed pattern noisefrom the input interference signal. Next, the image generating portion147 performs desired window function processing in order to optimize thedepth resolution and the dynamic range that have a trade-offrelationship when Fourier transform is performed at a finite interval.After that, the image generating portion 147 performs FFT processing togenerate the luminance image of the tomographic image.

After the luminance image generation, in Step S260, the signalprocessing portion 144 increments the index j of the data on therepeated B-scans to be extracted. In Step S270, the signal processingportion 144 determines whether or not the number of extracted pieces ofB-scan data is larger than m. That is, the signal processing portion 144determines whether or not the generation of the luminance image based onthe B-scan data at the position yi has been repeated m times. When thegeneration of the luminance image has not reached m times, the flowreturns to Step S240 to repeat the generation of the luminance imagebased on the B-scan data obtained by the repeated B-scans at the sameposition yi. That is, the image generating portion 147 repeats theprocessing from Step S240 to Step S260 to acquire a plurality ofluminance images (tomographic images) at substantially the same locationof the eye 118.

When it is determined in Step S270 that the generation of the luminanceimage has reached m times, the flow proceeds to Step S280. In Step S280,the signal processing portion 144 performs position alignment of the mframes of the luminance image at the same position yi obtained in theabove-mentioned steps from Step S240 to Step S260. Specifically, thesignal processing portion 144 first selects one arbitrary frame from them frames as a luminance image for a template. The frame to be selectedas a template may be selected by calculating correlations in all of thecombinations, obtaining the sum of correlation coefficients for eachframe, and selecting the frame having the maximum sum.

Next, the signal processing portion 144 obtains misalignment amounts(δX, δY, and δθ) by comparing the template with each frame.Specifically, the signal processing portion 144 calculates a normalizedcross-correlation (NCC) that is an index representing a similarity withthe image of the frame to be compared with while changing the positionand the angle of the template image, and obtains as the misalignmentamounts a difference of an image position exhibited when the value ofNCC is the maximum. The signal processing portion 144 further appliesposition correction to the (m−1) frames other than the template inaccordance with the misalignment amounts (δX, δY, and δθ), to therebyperform the position alignment of the m frames.

Various changes can be made to the index representing the similarity aslong as the index is a scale representing the similarity betweencharacteristics of the images in the template and the frame. Forexample, a sum of absolute difference (SAD), a sum of squared difference(SSD), or a zero-means normalized cross-correlation (ZNCC) may be used.Further, a phase only correlation (POC) or a rotation invariant phaseonly correlation (RIPOC) may be used.

After the position alignment of the m frames is completed, in Step S290,the signal processing portion 144 averages the luminance imagessubjected to the position alignment in Step S280 to generate an averagedluminance image. The averaged luminance image is used at a time ofthreshold processing described later. As the mode of the averaging, theaveraging may be executed by combining at least two interference signalsets corresponding to a plurality of frames in a superimposed manner.

After the averaged luminance image is generated, in Step S310, the imagegenerating portion 147 executes the calculation of the motion contrast.In this embodiment, a dispersion value of a signal intensity (luminance)is calculated for each pixel at the same position from the m frames ofthe luminance image subjected to the position alignment by the signalprocessing portion 144 in Step S280, and this dispersion value is set asthe motion contrast. That is, the image generating portion 147calculates the motion contrast through use of pixel data on thecorresponding pixels among the respective plurality of luminance imagesat the same position. Other than the dispersion value, any one of astandard deviation, a difference value, a decorrelation value, and acorrelation value may be used. That is, any index representing a changein luminance value among the respective pixels of a plurality of B-scanimages at the same y-position can be used as the motion contrast.Further, the phase may be used instead of the signal intensity.

The motion contrast can also use a variation coefficient that isnormalized by an average value of each pixel at the same position ineach frame, instead of the dispersion value of each pixel at the sameposition in the luminance images of the m frames of tomographic images.In this case, the motion contrast is independent of the pixel valuesindicating the structure of a retina, and it is possible to obtain amotion contrast having higher sensitivity.

In Step S320, the signal processing portion 144 performs thresholdprocessing on the calculated motion contrast. In this embodiment, thesignal processing portion 144 extracts an area in which only randomnoise is displayed from the averaged luminance image calculated in StepS310, and calculates a standard deviation σ for the area to set“(averaged luminance of noise floor)+2σ” as a threshold value. Thesignal processing portion 144 sets the value of the motion contrast of apixel having a luminance value equal to or smaller than the thresholdvalue to 0 to disable the pixel data. By the threshold processing ofStep S320, it is possible to remove the motion contrast derived from achange in luminance due to the random noise, and to reduce noise.

As the threshold value becomes smaller, a detection sensitivity for themotion contrast increases, and noise components also increase. Incontrast, as the threshold value becomes larger, the noise componentsdecrease, but the detection sensitivity for the motion contrast islowered. In view of the above-mentioned fact, the threshold value is setto “(averaged luminance of noise floor)+2σ” in this embodiment, but thethreshold value is not limited thereto.

After the threshold processing is completed, in Step S330, the signalprocessing portion 144 increments the index i of the position yi. InStep S340, the signal processing portion 144 determines whether or not iis larger than n. That is, the signal processing portion 144 determineswhether or not the position alignment, the generation of the averagedluminance image, the calculation of the motion contrast, and thethreshold processing have been completed at all of the n y-positions.When there is a y-position at which the processing has not beencompleted, the flow returns to Step S220. After that, those pieces ofprocessing are repeated until the processing from Step S220 to Step S330has been completed at all of the y-positions. When all the pieces ofprocessing have been completed, the flow proceeds to the next Step S350.

In Step S340, it is determined whether or not i has become larger than nand the above-mentioned processing has been completed at all of they-positions. When the processing has been completed, the averagedluminance images have been generated and the motion contrasts have beenacquired for the B-scan images (luminance images in a retinal crosssection along the B-scan line) at all of the y-positions. The B-scanimages at a plurality of y-positions correspond to the 3-D tomographicimage data in a scan area of the measuring light, and the motioncontrast data obtained at those y-positions also corresponds to data inthree dimensions. As described above, the signal processing portion 144functions as a 3-D tomographic data generating unit configured togenerate the 3-D tomographic image data and a 3-D motion contrastgenerating unit configured to generate 3-D motion contrast data.

In Step S350, the signal processing portion 144 performs processing foracquiring a vessel wall thickness through use of 3-D data on the motioncontrast. After the vessel wall thickness is acquired, it is determinedthat the 3-D vessel information has been generated, and the processingillustrated in the flowchart is completed. Next, with reference to FIG.6, the processing for acquiring the vessel wall thickness to be executedin Step S350 is described in detail. FIG. 6 is a flow chart forillustrating processing for calculating the vessel wall thickness basedon the acquired data on the 3-D motion contrast and the luminance. Asdescribed above, in this embodiment, the 3-D tomographic image data andthe 3-D motion contrast data are pieces of data subjected to theposition alignment between the pixels corresponding to each other. Thesubsequent processing presupposes that the above-mentioned positionalignment of data has been completed.

[Procedure of Processing for Calculating Vessel Wall Thickness]

In Step S351, the signal processing portion 144 acquires the previouslyobtained 3-D tomographic image data (luminance image). In Step S352, thesignal processing portion 144 acquires the 3-D motion contrast data. Inthis embodiment, the 3-D tomographic image data and the 3-D motioncontrast data are obtained from the same B-scan data. Therefore, thescan area, the respective pixels in a 3-D space within the scan area,the spatial resolution (sample pitch), the depth resolution, and thelike are the same between both the pieces of data. Therefore, theposition alignment between both the pieces of data is considered to havealready been completed, and superimposition processing described lateror the like can be executed as it is in a manner of the flow chartillustrated in FIG. 6.

However, the 3-D tomographic image data and the 3-D motion contrast datamay be obtained from B-scans that are different from each other. Forexample, when the 3-D tomographic image data is acquired, a scan rangeof the B-scan relating to the same cross section is set larger than ascan range of the B-scan performed to acquire the 3-D motion contrastdata, and the acquisition may be executed as each individual scan.Further, it is preferred that the processing for averaging be performedwhen the 3-D tomographic image data is acquired, but in this case, the3-D tomographic image data may be obtained by one B-scan and one C-scan.Also in this case, the 3-D tomographic image data and the 3-D motioncontrast data may be normalized so as to have an equal resolution, andthe position alignment may be further performed. By such pre-processing,the subsequent processing within the flow chart illustrated in FIG. 6can be performed in the same manner.

(Vessel Candidate Extracting Processing)

The signal processing portion 144 can extract a vessel candidate fromthe 3-D tomographic image data or the 3-D motion contrast data. Toextract the vessel candidate, luminance information on the 3-Dtomographic image data may be used, or the motion contrast informationmay be used. In this embodiment, as illustrated in FIG. 6, in Step S353,the signal processing portion 144 extracts the vessel candidate throughuse of the 3-D motion contrast data. At that time, the signal processingportion 144 performs the threshold processing on the data on therespective pixels, and recognizes, as a pixel of the vessel candidate, apixel indicating data having the 3-D motion contrast data equal to orlarger than a predetermined threshold value. Also when the 3-Dtomographic image data is used, the signal processing portion 144performs the threshold processing on the data on the respective pixels,and recognizes the pixel of the vessel candidate.

The pieces of data evaluated as the vessel candidate at this time mayinclude data derived from random noise and data on a minute vessel thatdoes not correspond to an object to be measured. In order to effectivelyavoid those pieces of data, it is desired to take the connectiverelationship between vessels into consideration. Hence, the number ofsuccessive pixels in terms of the motion contrast data among therespective vessel candidates is evaluated to estimate the connectivityof the vessel from the length in number of pixels. That is, it ispossible to automatically extract a vessel candidate useful as an objectto be measured by separately designating a threshold value relating tothe number of successive pixels in a case where pixels exceeding apredetermined threshold value are successively arranged, and recognizingthat a pixel group, which is included in the successive pixels evaluatedas a vessel candidate and has a connection including a predeterminednumber or more of pixels, indicates a vessel. That is, a vesselextracting unit recognizes, as a vessel, the above-mentioned pixel groupbeing the pixels of the vessel candidate and including a predeterminednumber or more of successive pixels.

(Generation and Display of 2-D Image)

After the vessel candidate is extracted, in Step S354, the mapgenerating portion 148 performs segmentation processing. Specifically,the map generating portion 148 identifies each layer in the retina byperforming comparison processing between a luminance profile of the 3-Dtomographic image data in the depth direction and a threshold valuecorresponding to each layer or a layer boundary. After theidentification, the values of respective pixels within a specific layerinterval or within a predetermined range in the depth direction areprojected or integrated in the depth direction to generate 2-D imagedata. In addition, a 2-D image referred to as an enface luminance imageis generated based on the 2-D image data. In this embodiment, therespective pixels for presenting the 3-D motion contrast data correspondto the respective pixels for presenting the 3-D tomographic image data.Therefore, the same processing is also performed for the 3-D motioncontrast data to generate 2-D motion contrast data. At that time, dataon pixels, the number of which is equal to or smaller than theabove-mentioned predetermined threshold value, is disabled because ofbeing determined as pixels corresponding to a tissue that does notinclude a vessel, and the value of the motion contrast is set to, forexample, 0. It is possible to more clearly present information relatingto blood flow in a 3-D space by generating the 2-D motion contrast dataincluding the pixel of the disabled data. At the same time, a 2-D motioncontrast enface image corresponding to the enface luminance image isgenerated based on the 2-D motion contrast data.

In OCTA, a constituent existing in the blood flow, namely, a lumen ofthe vessel is extracted. The retinal vessel wall is substantiallytransparent, and hence a subject to be extracted in another angiographyis the same. Meanwhile, the luminance image obtained by the OCTapparatus is obtained by detecting reflection or scattering due to theouter surface of the vessel wall as the interference light. Hence, theinner surface structure of the vessel wall in contact with blood can beextracted from the motion contrast image, and the outer surfacestructure of the vessel wall can be extracted from the luminance image.Therefore, the vessel matched in both the images is set as a vessel tobe measured being the object to be measured, and a difference betweenthe two images regarding the vessel is obtained, to thereby be able toacquire information on a vessel wall thickness useful for diagnosis.

The generated 2-D motion contrast enface image exemplified in FIG. 8 isdisplayed on the display portion 146 by the display control portion 149.When the vessel candidate can be extracted and recognized from theimage, a 2-D enface luminance image may be displayed on the displayportion 146. In this embodiment, in order to generate the enfaceluminance image or the 2-D motion contrast enface image, thecorresponding pixel values are integrated. However, the enface luminanceimage can also be generated by extracting representative values, forexample, maximum values, minimum values, and median values of therespective pixel values and projecting or integrating the representativevalues. In this embodiment, only the 2-D motion contrast enface image isdisplayed, but both the 2-D motion contrast enface image and the enfaceluminance image may be displayed in different colors in a superimposedmanner as the need arises.

(Marker Processing and Display of Designation Image)

After the 2-D image is displayed, in Step S355, the signal processingportion 144 instructs the display control portion 149 to highlight theextracted vessel candidate on the display screen by adding a marker. Thehighlight using the marker allows the user to be notified of thelocation of the extracted vessel. Specifically, the 2-D motion contrastenface image is displayed on the display portion 146, and the markerindicating the vessel candidate is further displayed at a pixelcoordinate corresponding to the vessel candidate extracted from the 3-Dmotion contrast data in a superimposed manner so as to enable eachvessel candidate to be identified. FIG. 9 is an example of display onthe display portion 146, and the image of FIG. 9 serves as a designationimage for designating a vessel having a wall thickness to be measuredand a region on the vessel. In the display example, M1, M2, . . . , andMn are the markers of all the extracted vessels. On the display screen,a mouse cursor MC is displayed in a superimposed manner. In thisembodiment, the display portion 146 corresponds to a display unitconfigured to display at least one of the 2-D image and the 2-D motioncontrast image (enface luminance image and 2-D motion contrast enfaceimage). The display control portion 149 corresponds to a unit configuredto display the above-mentioned display mode for designating a region tobe measured on the display portion 146, to receive a designation commandinput to the display mode, and to input the designation to the signalprocessing portion 144.

(Designation of Vessel to be Measured and Region to be Measured)

In Step S356, the user recognizes the displayed marker as the extractedvessel, and designates a region on the marker where the vessel wallthickness is to be measured by clicking on the region with a pointingdevice, for example, a mouse. An exemplary UI thereof is describedbelow. First, when the user moves the mouse cursor MC closer to themarker corresponding to a desired vessel candidate, only that marker ishighlighted, and even overlapping vessels, for example, can bedistinguished from each other. In this case, the user moves the mousecursor MC to a position approximately close to the region on thehighlighted marker where the wall thickness is to be measured. When aclick is performed with the mouse in this state, a frame 7 c asillustrated in, for example, FIG. 7, is displayed. At the same time,markers at two points of an outer surface coordinate and an innersurface coordinate are displayed as points of measurement of the vesselwall thickness. When the user further performs a click with the mouseunder this state, the selection of the region to be measured isdetermined.

As described later, the measurement of the vessel wall thickness at thedesignated position is executed in the following flow. However, whenboth the 2-D motion contrast enface image and the enface luminance imageare superimposed on each other and a desired vessel region is furthermagnified, it is possible to intuitively recognize the structure of theinner surface and the outer surface of the vessel wall without measuringthe image. For example, the vicinity of the region where the vessel wallthickness is to be measured may be highly magnified as illustrated inFIG. 7 and may be displayed once a click is performed with the mouseafter the mouse cursor MC is put in the vicinity of the region to bemeasured. The superimposition of images (superimposition processing) andthe magnification processing can facilitate the grasp of an innersurface 7 b of the vessel wall (motion contrast enface image) and anouter surface 7 a of the vessel wall (enface luminance image) within the2-D image. In this case, when two points corresponding to an innersurface point 7 b′ and an outer surface point 7 a′ of the vessel in theregion to be measured, which are visually recognized on the 2-D image,are designated and a distance between the two points is measured, thevessel wall thickness at the position can also be uniquely obtained. Itis also possible to easily obtain the wall thickness with more accuracyby designating four points along a cutting-plane line substantiallyorthogonal to the vessel wall as a cross section of the vessel, andmeasuring a distance between points that form a pair.

(Calculation of Measured Cross Section)

However, in an actual case, the distance between two individuallydesignated points does not easily match the vessel wall thickness in theregion with accuracy. In order to correctly obtain the vessel wallthickness, it is necessary to define a cross section orthogonal to avessel travel direction in the vicinity of the above-mentioned region tobe measured. In this embodiment, in Step S357, a result of estimatingthe above-mentioned connectivity of the vessel is used. That is, whenthere are at least two pixels, desirably at least three pixels, ofconnective data, an average connective direction of those pixels ishandled as a vector to obtain a direction vector from a difference in X,Y, and Z coordinates. This direction vector is defined as the vesseltravel direction. In addition, when a consideration is given to a planeorthogonal to the vessel travel direction at one pixel coordinate in avessel connective portion, this plane can be defined as thecross-section of the vessel.

FIG. 10 is a diagram for illustrating a method of determining a measuredcross section. In FIG. 10, the vessel to be measured is represented byB, a target pixel on the vessel B is represented by P1, and a pixelconnected to P1 is represented by P2. The respective pixel coordinatesof P1 and P2 are set as (x1, y1, z1) and (x2, y2, z2). In this case, avector V indicating the vessel travel direction is defined as (x2−x1,y2−y1, z2−z1). When the plane having the vector V as a normal isrepresented by C, an orthogonal plane being the measured cross sectioncan be uniquely defined. The cross section is superimposed as thecutting-plane line on the magnified image illustrated in FIG. 7, and adistance between intersection points between the cutting-plane line andthe outer surface 7 a of the vessel wall and between the cutting-planeline and an inner surface 7 b of the vessel wall is measured, to therebyallow the vessel wall thickness in this region to be known withaccuracy.

(Calculation of Outer Surface Coordinate and Inner Surface Coordinate)

In Step S358, the signal processing portion 144 calculates thecoordinate of an inner surface of the vessel wall. Regarding thecalculation, the motion contrast data corresponding to the vessel crosssection is generated from the 3-D motion contrast data, and thegenerated data is used to calculate the inner surface coordinate, tothereby allow a thickness of the vessel wall to be measured with ageometrically correct positional relationship. In the same manner,regarding the calculation of the coordinate of the outer surface of thevessel wall in Step S359, the tomographic image data corresponding tothe same vessel cross section may be generated from the 3-D tomographicimage data, and the generated data may be used to calculate the outersurface coordinate.

Next, specific description is given of processing for calculating theinner surface coordinate which is executed in Step S358. In Step S358,the inner surface structure of the same vessel wall as that of thevessel to be measured, which is previously extracted, is extracted fromthe 3-D motion contrast data acquired in Step S352. The inner surface ofthe vessel wall matches an outer periphery of blood (blood column)flowing through a vessel cavity. Hence, the inner surface structure ofthe same vessel wall of the vessel to be measured is obtained from themotion contrast data, and the inner surface coordinate on the measuredcross section is detected from the positional information on the edge.In this processing, the signal processing portion 144 functions as aninner surface coordinate detecting unit configured to detect thecoordinate of the inner surface of the vessel wall corresponding to theregion designated on the vessel to be measured.

Next, specific description is given of processing for calculating theouter surface coordinate executed in Step S359. In Step S359, the outersurface structure of the vessel wall of the vessel to be measured isextracted from the 3-D tomographic image data acquired in Step S351. Thevessel wall is substantially transparent, but the luminance imageacquired by the OCT apparatus is based on an intensity of reflectedlight generated from a difference in refractive index of the retinalstructure, and hence information on the outer surface of the vessel canbe acquired satisfactorily. Then, the coordinate of the outer surface ofthe vessel wall on the measured cross section is detected from thepositional information on the edge of the outer surface of the vesselwall. In this processing, the signal processing portion 144 functions asan outer surface coordinate detecting unit configured to detect thecoordinate of the outer surface of the vessel wall corresponding to theregion designated on the vessel to be measured.

When the motion contrast image is generated, each luminance is set sothat a pixel value for a motion contrast equal to or smaller than agiven threshold value is 0. Therefore, the given threshold value needsto be set appropriately in order to correctly detect the coordinate ofthe inner surface of the vessel wall. In this embodiment, in order toremove the motion contrast derived from the random noise, the thresholdvalue is set to “(averaged luminance)+2σ” based on the averagedluminance of the noise floor and the standard deviation σ of all theimages. However, the threshold value may be adjustable, or may bedetermined based on luminance information on a region (attention area)around the vessel to be measured.

(Calculation of Vessel Wall Thickness)

After calculating the inner surface coordinate and the outer surfacecoordinate, in Step S360, the signal processing portion 144 calculatesthe vessel wall thickness from the inner surface coordinate obtained inStep S358 and the outer surface coordinate obtained in Step S359. Asdescribed above with reference to FIG. 7, the outer surface 7 a of thevessel wall and the inner surface 7 b of the vessel wall represent theedges of the outer surface structure and the inner surface structure,respectively, of the vessel wall of the vessel to be measured, and therespective points of measurement corresponding to the same region arerepresented by the outer surface point 7 a′ and the inner surface point7 b′. A distance between the two points is equal to the thickness of thevessel wall, and hence the vessel wall thickness Δt is obtained bycalculating the distance. After the vessel wall thickness is calculated,the processing for calculating the vessel wall thickness is completed. Aresult of the calculation is displayed on the display screen illustratedin FIG. 7.

As described above, this embodiment provides an OCT data processingmethod for executing the above-mentioned various kinds of processing forOCT data obtained by the OCT apparatus to obtain information relating tothe vessel wall regarding the designated region on the vessel to bemeasured, more specifically, the inner surface coordinate and the outersurface coordinate. In this embodiment, the designation of the region tobe measured is performed via the display screen. However, in theprocessing for obtaining the measured cross section, a wall thickness ofthe vessel on an automatically determined measured cross section may becalculated, a ratio of a vessel diameter and the wall thickness on themeasured cross section may be compared with a predetermined value, andthe region to be measured may be automatically designated based on aresult of the comparison. Further, through display of the 2-D motioncontrast enface image and the enface luminance image in a superimposedmanner, it is possible to easily grasp the thickness of the vessel wallof each vessel simply as a distance between display parts of the twoimages along a direction orthogonal to the vessel wall. The region to bemeasured may be automatically designated from a ratio of theabove-mentioned distance and a distance between the edges of the imagecorresponding to the vessel on the 2-D motion contrast enface image orthe enface luminance image along the orthogonal direction. Whenreceiving an instruction for the designation performed automatically,the signal processing portion 144 executes the above-mentionedprocessing for calculating the vessel wall thickness.

(3-D Data Processing)

In the description given above, the vessel wall thickness is measured asthe distance between the two points 7 a′ and 7 b′ on the superimpositionimage of the 2-D motion contrast enface image and the enface luminanceimage, which is exemplified in FIG. 7. However, the vessel is actuallytubular tissue, and it is conceivable that a state of the vessel cannotbe accurately grasped from the displayed image. Therefore, it is desiredto grasp the wall thickness for the entire perimeter of the vessel inthe designated region. For example, in a case of a model displayed inFIG. 10, the coordinate of P1 within a plane C is estimated as a centerposition of the vessel. The 3-D motion contrast data and the 3-Dtomographic image data have already been acquired. Throughreconstruction of those pieces of data within the plane C, it is alsopossible to generate, for example, a tubular vessel cross section image.Therefore, a difference in distance between the inner surface of thevessel wall and the outer surface of the vessel wall is obtained fromthe coordinate of P1, to thereby obtain dimensional information relatingto the vessel wall in the designated region.

In this case, it is preferred that the 3-D image of the vessel obtainedthrough the superimposition of the 3-D motion contrast data and the 3-Dtomographic image data be displayed as a screen for displaying theresults. More specifically, the designated vessel, the designated regionon the designated vessel, and its vicinity may be highly magnified to bethree-dimensionally displayed as a vessel cross-sectional view, and thenumerical values of the average thickness, minimum thickness, maximumthickness, standard deviation, and the like of the vessel wall in thedesignated region may be further displayed in a superimposed manner. Inthe case of this embodiment, the 3-D motion contrast data and the 3-Dtomographic image data have already been acquired in advance, and hencethe displayed results can also be changed as the region to be measuredis moved on a designation screen for the region to be measured.

(Measurement of Plurality of Successive Cross Sections)

In actual diagnosis of a vessel, it is important to evaluate continuityof the travel of the vessel. In the above-mentioned embodiment, oneorthogonal plane is set as the cross section for obtaining the vesselwall thickness. However, at least three proximal orthogonal planescorresponding to the connected pixels may be defined to generate thetomographic image data and the motion contrast data that correspond tothose planes. In this case, through the same processing as theabove-mentioned processing for each of the planes, it is possible todetect a plurality of successive outer surface coordinates andsuccessive inner surface coordinates. In addition, successive vesselwall thicknesses can be calculated from distances between the outersurface coordinates and the inner surface coordinates being results ofthe detection. It is also possible to designate a start point and an endpoint of the measurement on the vessel, to define orthogonal planesproximal to each other at an interval defined in advance, and tocalculate the vessel wall thicknesses on the designated sections.

(Trend Prediction)

As described above, a trend in change of the vessel wall thicknesses canbe predicted based on the information on the successive vessel wallthicknesses. FIG. 11 is an example in which a part of the vessel wall ofa given vessel exhibits hypertrophy to be clogged. In FIG. 11, planesC1, C2, and C3 are respectively orthogonal to the travel of the vesselsuccessive with pixel pitches for connecting the respective planes, andvessel wall thicknesses E1, E2, and E3 are calculated assuming thatthose planes are the respective cross sections. When the vessel wallthicknesses E1, E2, and E3 are successfully obtained, it is possible topredict a wall thickness E4′ on a cross section C4 defined from the nextconnected pixels. A method for the prediction exhibits higher accuracyas the number of pieces of data becomes larger. For example, asecond-order extrapolation is used when the number of pieces of knowndata is 3 points, and a third-order extrapolation is used when thenumber of pieces of known data is 4 points. In this example, the trendis predicted by the second-order extrapolation using 3 points as thenumber of order that can express a curved line to a minimum.

Subsequently, a wall thickness E4 on the cross section C4 is actuallycalculated against the obtained result of the prediction. In the exampleof FIG. 11, the vessel wall on a C4 cross section discontinuouslyexhibits abrupt hypertrophy, and hence the actual wall thickness E4 islarger than the predicted wall thickness E4′. A larger differencebetween E4 and E4′ indicates that the continuity of the vessel wall islower, and can be determined to exhibit a higher correlation with anabnormality in the vessel wall. Therefore, it is possible to detect anabnormal region and an abnormality amount of the vessel wall byobtaining the difference between E4 and E4′. In this case, a case wherethe wall thickness becomes larger is described as the abnormality in thevessel wall, but the abnormal region that can be detected is not limitedto this mode, and also includes a case where the wall thickness becomesabruptly thinner and a case where plaque adheres to the inner surface ofthe vessel wall.

As described above, through use of the intensity image data and themotion contrast data obtained by the OCT apparatus as in thisembodiment, it is possible to acquire the information relating to thevessel wall of the retina and measure the wall thickness in a simplifiedmanner. In addition, it is further possible to extract the vessel traveldirection, and also possible to detect an abnormal location in thevessel in terms of shape, with the result that it is possible to providethe information on the vessel useful for diagnosis.

OTHER EMBODIMENTS

Embodiment(s) of the present disclosure can also be realized by acomputer of a system or apparatus that reads out and executes computerexecutable instructions (e.g., one or more programs) recorded on astorage medium (which may also be referred to more fully as a‘non-transitory computer-readable storage medium’) to perform thefunctions of one or more of the above-described embodiment(s) and/orthat includes one or more circuits (e.g., application specificintegrated circuit (ASIC)) for performing the functions of one or moreof the above-described embodiment(s), and by a method performed by thecomputer of the system or apparatus by, for example, reading out andexecuting the computer executable instructions from the storage mediumto perform the functions of one or more of the above-describedembodiment(s) and/or controlling the one or more circuits to perform thefunctions of one or more of the above-described embodiment(s). Thecomputer may comprise one or more processors (e.g., central processingunit (CPU), micro processing unit (MPU)) and may include a network ofseparate computers or separate processors to read out and execute thecomputer executable instructions. The computer executable instructionsmay be provided to the computer, for example, from a network or thestorage medium. The storage medium may include, for example, one or moreof a hard disk, a random-access memory (RAM), a read only memory (ROM),a storage of distributed computing systems, an optical disk (such as acompact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™),a flash memory device, a memory card, and the like.

While the present disclosure has been described with reference toexemplary embodiments, it is to be understood that the disclosure is notlimited to the disclosed exemplary embodiments. The scope of thefollowing claims is to be accorded the broadest interpretation so as toencompass all such modifications and equivalent structures andfunctions.

This application claims the benefit of Japanese Patent Application No.2016-044253, filed Mar. 8, 2016, which is hereby incorporated byreference herein in its entirety.

What is claimed is:
 1. An OCT data processing method, comprising:acquiring interference signal sets of a plurality of frames includinginterference signal sets corresponding to a plurality of frames thatform an image of the same cross section of an object to be inspected;generating 3-D tomographic image data on the object to be inspected fromthe interference signal sets of the plurality of frames; generating 3-Dmotion contrast data based on a pixel with time modulation in the objectto be inspected from the interference signal sets corresponding to theplurality of frames that form the same cross section; extracting avessel from the object to be inspected based on one of the 3-Dtomographic image data and the 3-D motion contrast data; detecting acoordinate of an outer surface of a vessel wall of the extracted vesselbased on the generated 3-D tomographic image data; and detecting acoordinate of an inner surface of the vessel wall of the extractedvessel based on the generated 3-D motion contrast data.
 2. An OCT dataprocessing method according to claim 1, wherein the acquiring theinterference signal comprises acquiring the interference signal setscorresponding to the plurality of frames that form the same crosssection when the interference signal sets of the plurality of frames areacquired.
 3. An OCT data processing method according to claim 2, whereinthe generating of the 3-D tomographic image data on the object to beinspected comprises combining at least two interference signal setscorresponding to the plurality of frames that form the same crosssection in a superimposed manner.
 4. An OCT data processing methodaccording to claim 1, wherein: the acquiring the interference signalcomprises acquiring the interference signal sets corresponding to theplurality of frames that form the same cross section and acquiringinterference signal sets of the plurality of frames excluding theinterference signal sets corresponding to the plurality of frames thatform the same cross section, the two signal acquiring steps beingdifferent from each other; wherein the 3-D tomographic image data isgenerated based on the interference signal sets of the plurality offrames excluding the interference signal sets corresponding to theplurality of frames that form the same cross section.
 5. An OCT dataprocessing method according to claim 4, further comprising performingposition alignment between the 3-D tomographic image data and the 3-Dmotion contrast data before the vessel is extracted.
 6. An OCT dataprocessing method according to claim 1, further comprising: generatingan enface luminance image by integrating the generated 3-D tomographicimage data in a depth direction within a predetermined range of thedepth direction; generating a 2-D motion contrast enface image byintegrating the generated 3-D motion contrast data in the depthdirection within a predetermined range of the depth direction; anddisplaying at least one of the enface luminance image or the 2-D motioncontrast enface image.
 7. An OCT data processing method according toclaim 6, further comprising receiving input of a region for detectingthe coordinate of the outer surface of the vessel wall and thecoordinate of the inner surface of the vessel wall in the displayed atleast one of the enface luminance image or the 2-D motion contrastenface image.
 8. An OCT data processing method according to claim 6,wherein the generating of the 2-D motion contrast enface imagecomprises: disabling data on a pixel having a value equal to or smallerthan a predetermined threshold value; and generating 2-D motion contrastdata by including the pixel of the disabled data.
 9. An OCT dataprocessing method according to claim 6, wherein the displaying comprisesdisplaying the 2-D motion contrast enface image and the enface luminanceimage in a superimposed manner.
 10. An OCT data processing methodaccording to claim 6, further comprising displaying a distance betweenat least two points designated on the vessel in an image obtained bydisplaying the 2-D motion contrast enface image and the enface luminanceimage in a superimposed manner.
 11. An OCT data processing methodaccording to claim 1, wherein the extracting of the vessel comprises:setting, as a pixel of a vessel candidate, a pixel having a value of the3-D motion contrast data equal to or larger than a predeterminedthreshold value; and estimating, as the vessel, a pixel group includinga predetermined number or more of successively arranged pixels of thevessel candidate.
 12. An OCT data processing method according to claim6, wherein: the extracting of the vessel comprises: setting, as a pixelof a vessel candidate, a pixel having a value of the 3-D motion contrastdata equal to or larger than a predetermined threshold value; andrecognizing, as the vessel, a pixel group including a predeterminednumber or more of successively arranged pixels of the vessel candidate;the displaying comprises displaying a marker for indicating the pixelgroup recognized as the vessel in one of a 2-D image and the 2-D motioncontrast enface image in a superimposed manner; and the extracting ofthe vessel further comprises inputting designation of the vessel throughselection of the displayed marker.
 13. An OCT data processing methodaccording to claim 11, further comprising defining a direction in whichthe pixels of the pixel group estimated as the vessel are successivelyarranged as a vessel travel direction, and defining a plane orthogonalto the vessel travel direction for pixels corresponding to a regiondesignated in the pixel group, wherein: the detecting of the coordinateof the outer surface comprises calculating the coordinate of the outersurface through use of tomographic image data generated from the 3-Dtomographic image data along the defined plane; and the detecting of thecoordinate of the inner surface comprises calculating the coordinate ofthe inner surface through use of motion contrast data generated from the3-D motion contrast data along the defined plane.
 14. An OCT dataprocessing method according to claim 13, wherein: the defining of theplane comprises defining at least three planes corresponding to pitchesfor connecting pixels; and the coordinate of the outer surface and thecoordinate of the inner surface are calculated for each of the at leastthree planes.
 15. An OCT data processing method according to claim 1,further comprising calculating a wall thickness of the vessel from thecoordinate of the outer surface and the coordinate of the inner surfacethat have been detected.
 16. An OCT data processing method according toclaim 12, wherein the detecting of the coordinate of the outer surfaceand the detecting of the coordinate of the inner surface comprisedetecting a plurality of coordinates of the outer surface and aplurality of coordinates of the inner surface, which are arranged in adirection for connecting the pixels of the pixel group on the extractedvessel, based on a state in which the pixels of the pixel group on theextracted vessel are connected.
 17. An OCT data processing methodaccording to claim 16, further comprising calculating a wall thicknessof the vessel from the coordinate of the outer surface and thecoordinate of the inner surface that have been detected.
 18. An OCT dataprocessing method according to claim 17, wherein the calculating of thewall thickness of the vessel comprises: calculating a trend in change ofsuccessive vessel wall thicknesses of the vessel; and detecting one ofan abnormality amount and an abnormal region of the vessel wall from thetrend in change of the vessel wall thicknesses and a difference betweenthe successive vessel wall thicknesses.
 19. A storage medium havingstored thereon a program for causing a computer to execute each step ofthe OCT data processing method of claim
 1. 20. An OCT data processingdevice, comprising: a signal acquiring unit configured to acquireinterference signal sets of a plurality of frames including interferencesignal sets corresponding to a plurality of frames that form an image ofthe same cross section of an object to be inspected; a 3-D tomographicdata generating unit configured to generate 3-D tomographic image dataon the object to be inspected from the interference signal sets of theplurality of frames; a 3-D motion contrast generating unit configured togenerate 3-D motion contrast data based on a pixel with time modulationin the object to be inspected from the interference signal setscorresponding to the plurality of frames that form the same crosssection; a vessel extracting unit configured to extract a vessel fromthe object to be inspected based on one of the 3-D tomographic imagedata and the 3-D motion contrast data; an outer surface coordinatedetecting unit configured to detect a coordinate of an outer surface ofa vessel wall of the extracted vessel based on the generated 3-Dtomographic image data; and an inner surface coordinate detecting unitconfigured to detect a coordinate of an inner surface of the vessel wallof the extracted vessel based on the generated 3-D motion contrast data.